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Record W4403993071 · doi:10.1029/2023wr037020

The Potential of Hydrogeodesy to Address Water‐Related and Sustainability Challenges

2024· article· en· W4403993071 on OpenAlexaff
Fernando Jaramillo, Saeid Aminjafari, Pascal Castellazzi, Ayan Santos Fleischmann, Etienne Fluet‐Chouinard, Hossein Hashemi, Clara Hübinger, Hilary R. Martens, Fabrice Papa, Tilo Schöne, Angelica Tarpanelli, Vili Virkki, Lan Wang‐Erlandsson, Rodrigo Abarca-del-Río, A. A. Borsa, Georgia Destouni, Giuliano Di Baldassarre, Michele‐Lee Moore, José A Posada-Marín, Shimon Wdowinski, Susanna Werth, George H. Allen, Donald F. Argus, Omid Elmi, Luciana Fenoglio-Marc, Frédéric Frappart, Xander Huggins, Zahra Kalantari, Simon Munier, Sebastián Palomino‐Ángel, Abigail Robinson, Kristian Rubiano, Gabriela Siles, Marc Simard, Chunqiao Song, Christopher Spence, Mohammad J. Tourian, Yoshihide Wada, Chao Wang, Jida Wang, Fangfang Yao, Wouter R. Berghuijs, Jean‐François Crétaux, J. S. Famiglietti, Alice César Fassoni‐Andrade, Jessica V. Fayne, Félix Girard, Matti Kummu, Kristine M. Larson, Martin Marañon, Daniel Medeiros Moreira, Karina Nielsen, Tamlin M. Pavelsky, Francisco J. Peña, J. T. Reager, Maria Cristina Rulli, Juan F. Salazar

Bibliographic record

VenueWater Resources Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsEnvironment and Climate Change CanadaUniversité LavalUniversity of Victoria
FundersSwedish National Space AgencyVetenskapsrådetJapan Aerospace Exploration AgencyCentre National d’Etudes SpatialesEuropean CommissionNational Aeronautics and Space Administration
KeywordsSustainabilityEnvironmental planningBusinessEnvironmental scienceEnvironmental resource managementWater resource management

Abstract

fetched live from OpenAlex

Abstract Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water‐related and sustainability sciences. Addressing this need, we combine a meta‐analysis of over 3,000 articles to chart the range, trends, and applications of satellite‐based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta‐analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water‐related and sustainability sciences in order to exploit its full potential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.312
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations35
Published2024
Admission routes1
Has abstractyes

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